python - Numpy Compare unequal rows and make both array of same dimension -

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a=    [[43655,    1428,     0, 2554]       [44580,  1428,     0,  2555]   [44930,  1428,     0,  2556]   [47708,  1428,     0,  2557]]      b=    [[41641,  1428,     0, 2554]   [44075,  1428,     0,  2555]   [44901,  1428,     1,  2556]   [45377,  1428,     0,  2557]   [48056,  1428,     0,  2558]]   new  b=  [[41641,  1428,     0, 2554]   [44075,  1428,     0,  2555]   [44901,  1428,     1,  2556]   [45377,  1428,     0,  2557]

i have 2 numpy array unequal rows. eg. array a has 4 rows while array b has 5 rows.
edit: no. of rows in array 'b' greater array 'a'. every element of a[:,3] lies in b[:,3]. there function extract rows of array b b[:,3]=a[:,3]

you can compare elements of 3rd column using zip , np.equal within list comprehension convert result numpy array , desire rows array b. 

>>> b[np.array([np.equal(*i) in zip(a[:,3],b[:,3])])] array([[41641,  1428,     0,  2554],        [44075,  1428,     0,  2555],        [44901,  1428,     1,  2556],        [45377,  1428,     0,  2557]])

if order not important you can use np.in1d :

>>> b[np.in1d(b[:,3],a[:,3])] array([[41641,  1428,     0,  2554],        [44075,  1428,     0,  2555],        [44901,  1428,     1,  2556],        [45377,  1428,     0,  2557]])  >>> a=np.array([[100, 1], [101, 4], [106, 6], [104, 10]]) >>> b= np.array([[ 1, 1], [ 2, 2], [ 3, 3], [ 4, 4], [ 5, 5], [ 6, 6], [ 7, 7], [ 8, 8], [ 9, 9], [10, 10]]) >>>  >>> b[np.in1d(b[:,1],a[:,1])] array([[ 1,  1],        [ 4,  4],        [ 6,  6],        [10, 10]])

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